Overview

Brought to you by YData

Dataset statistics

Number of variables18
Number of observations818
Missing cells3
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory918.5 KiB
Average record size in memory1.1 KiB

Variable types

Text6
URL1
Numeric5
DateTime3
Boolean2
Categorical1

Alerts

nsfw has constant value "False"Constant
Predicted post score is highly overall correlated with Time Since PostHigh correlation
Time Since Post is highly overall correlated with Predicted post scoreHigh correlation
is_credible is highly overall correlated with number of comments and 1 other fieldsHigh correlation
number of comments is highly overall correlated with is_credible and 1 other fieldsHigh correlation
post score is highly overall correlated with is_credible and 1 other fieldsHigh correlation
spam flag is highly imbalanced (58.2%)Imbalance
comment id has unique valuesUnique
post score has 145 (17.7%) zerosZeros
comment score has 15 (1.8%) zerosZeros

Reproduction

Analysis started2024-12-10 16:58:09.328874
Analysis finished2024-12-10 16:58:15.374133
Duration6.05 seconds
Software versionydata-profiling vv4.10.0
Download configurationconfig.json

Variables

Distinct124
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size51.2 KiB
2024-12-10T22:28:15.653668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters5726
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)5.4%

Sample

1st row1h8qy7p
2nd row1h8qy7p
3rd row1h8qth1
4th row1h8qq89
5th row1h8qq89
ValueCountFrequency (%)
1h7sjyt 57
 
7.0%
1h88j4n 51
 
6.2%
1h88zcr 51
 
6.2%
1h8bznq 44
 
5.4%
1h8pu61 36
 
4.4%
1h8dgcc 26
 
3.2%
1h7rzi5 26
 
3.2%
1h7qzcj 20
 
2.4%
1h7smdx 20
 
2.4%
1h7wql2 19
 
2.3%
Other values (114) 468
57.2%
2024-12-10T22:28:16.120204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
h 897
15.7%
1 868
15.2%
8 745
 
13.0%
7 278
 
4.9%
z 203
 
3.5%
c 183
 
3.2%
j 169
 
3.0%
n 157
 
2.7%
g 154
 
2.7%
s 127
 
2.2%
Other values (26) 1945
34.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5726
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
h 897
15.7%
1 868
15.2%
8 745
 
13.0%
7 278
 
4.9%
z 203
 
3.5%
c 183
 
3.2%
j 169
 
3.0%
n 157
 
2.7%
g 154
 
2.7%
s 127
 
2.2%
Other values (26) 1945
34.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5726
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
h 897
15.7%
1 868
15.2%
8 745
 
13.0%
7 278
 
4.9%
z 203
 
3.5%
c 183
 
3.2%
j 169
 
3.0%
n 157
 
2.7%
g 154
 
2.7%
s 127
 
2.2%
Other values (26) 1945
34.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5726
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
h 897
15.7%
1 868
15.2%
8 745
 
13.0%
7 278
 
4.9%
z 203
 
3.5%
c 183
 
3.2%
j 169
 
3.0%
n 157
 
2.7%
g 154
 
2.7%
s 127
 
2.2%
Other values (26) 1945
34.0%
Distinct113
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size119.5 KiB
2024-12-10T22:28:16.398277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length300
Median length148
Mean length83.177262
Min length12

Characters and Unicode

Total characters68039
Distinct characters106
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)3.8%

Sample

1st rowStruggling to Retain Rust Concepts – Looking for a Book or Resource with Progressive Exercises
2nd rowStruggling to Retain Rust Concepts – Looking for a Book or Resource with Progressive Exercises
3rd rowRecommended tech stack / approach for simple hobby project?
4th row "Starting a New YouTube Channel for Learning Programming: Join Us to Learn Coding from Scratch!"
5th row "Starting a New YouTube Channel for Learning Programming: Join Us to Learn Coding from Scratch!"
ValueCountFrequency (%)
531
 
4.9%
exam 257
 
2.4%
help 232
 
2.1%
test 209
 
1.9%
to 173
 
1.6%
for 153
 
1.4%
i 126
 
1.2%
reddit 106
 
1.0%
proctored 102
 
0.9%
prometric 102
 
0.9%
Other values (574) 8825
81.6%
2024-12-10T22:28:16.935657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10148
 
14.9%
e 5254
 
7.7%
o 3869
 
5.7%
r 3786
 
5.6%
a 3549
 
5.2%
t 3501
 
5.1%
i 3069
 
4.5%
n 2833
 
4.2%
s 2450
 
3.6%
c 1786
 
2.6%
Other values (96) 27794
40.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 68039
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
10148
 
14.9%
e 5254
 
7.7%
o 3869
 
5.7%
r 3786
 
5.6%
a 3549
 
5.2%
t 3501
 
5.1%
i 3069
 
4.5%
n 2833
 
4.2%
s 2450
 
3.6%
c 1786
 
2.6%
Other values (96) 27794
40.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 68039
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
10148
 
14.9%
e 5254
 
7.7%
o 3869
 
5.7%
r 3786
 
5.6%
a 3549
 
5.2%
t 3501
 
5.1%
i 3069
 
4.5%
n 2833
 
4.2%
s 2450
 
3.6%
c 1786
 
2.6%
Other values (96) 27794
40.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 68039
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
10148
 
14.9%
e 5254
 
7.7%
o 3869
 
5.7%
r 3786
 
5.6%
a 3549
 
5.2%
t 3501
 
5.1%
i 3069
 
4.5%
n 2833
 
4.2%
s 2450
 
3.6%
c 1786
 
2.6%
Other values (96) 27794
40.9%
Distinct124
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size118.5 KiB
https://www.reddit.com/r/LocalLLaMA/comments/1h7sjyt/windsurf_cascade_leaked_system_prompt/
 
57
https://www.reddit.com/r/Entranceexam_Reddit/comments/1h88zcr/online_proctored_test_help_prometric_kryterion/
 
51
https://www.reddit.com/r/proctoring/comments/1h88j4n/online_proctored_exam_help_test_takers_sat_math/
 
51
https://www.reddit.com/r/OMSCS/comments/1h8bznq/free_at_last_my_omscs_journey/
 
44
https://www.reddit.com/r/dataengineering/comments/1h8pu61/what_do_you_think_are_the_most_important_topics/
 
36
Other values (119)
579 
ValueCountFrequency (%)
https://www.reddit.com/r/LocalLLaMA/comments/1h7sjyt/windsurf_cascade_leaked_system_prompt/ 57
 
7.0%
https://www.reddit.com/r/Entranceexam_Reddit/comments/1h88zcr/online_proctored_test_help_prometric_kryterion/ 51
 
6.2%
https://www.reddit.com/r/proctoring/comments/1h88j4n/online_proctored_exam_help_test_takers_sat_math/ 51
 
6.2%
https://www.reddit.com/r/OMSCS/comments/1h8bznq/free_at_last_my_omscs_journey/ 44
 
5.4%
https://www.reddit.com/r/dataengineering/comments/1h8pu61/what_do_you_think_are_the_most_important_topics/ 36
 
4.4%
https://www.reddit.com/r/learnprogramming/comments/1h8dgcc/java_python_or_go/ 26
 
3.2%
https://www.reddit.com/r/cscareerquestions/comments/1h7rzi5/why_do_i_hate_other_languages_how_to_stop/ 26
 
3.2%
https://v.redd.it/jho9xmm5455e1 20
 
2.4%
https://www.reddit.com/r/django/comments/1h7smdx/build_web_management_app_for_car_repair_shop/ 20
 
2.4%
https://www.reddit.com/r/learnmachinelearning/comments/1h7wql2/feeling_overwhelmed_trying_to_learn_ml_any_tips/ 19
 
2.3%
Other values (114) 468
57.2%
ValueCountFrequency (%)
https 818
100.0%
ValueCountFrequency (%)
www.reddit.com 778
95.1%
v.redd.it 20
 
2.4%
i.redd.it 16
 
2.0%
www.jucktion.com 4
 
0.5%
ValueCountFrequency (%)
/r/LocalLLaMA/comments/1h7sjyt/windsurf_cascade_leaked_system_prompt/ 57
 
7.0%
/r/Entranceexam_Reddit/comments/1h88zcr/online_proctored_test_help_prometric_kryterion/ 51
 
6.2%
/r/proctoring/comments/1h88j4n/online_proctored_exam_help_test_takers_sat_math/ 51
 
6.2%
/r/OMSCS/comments/1h8bznq/free_at_last_my_omscs_journey/ 44
 
5.4%
/r/dataengineering/comments/1h8pu61/what_do_you_think_are_the_most_important_topics/ 36
 
4.4%
/r/learnprogramming/comments/1h8dgcc/java_python_or_go/ 26
 
3.2%
/r/cscareerquestions/comments/1h7rzi5/why_do_i_hate_other_languages_how_to_stop/ 26
 
3.2%
/jho9xmm5455e1 20
 
2.4%
/r/django/comments/1h7smdx/build_web_management_app_for_car_repair_shop/ 20
 
2.4%
/r/learnmachinelearning/comments/1h7wql2/feeling_overwhelmed_trying_to_learn_ml_any_tips/ 19
 
2.3%
Other values (114) 468
57.2%
ValueCountFrequency (%)
818
100.0%
ValueCountFrequency (%)
818
100.0%

post score
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.229829
Minimum0
Maximum187
Zeros145
Zeros (%)17.7%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-12-10T22:28:17.127210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median9
Q326
95-th percentile186
Maximum187
Range187
Interquartile range (IQR)25

Descriptive statistics

Standard deviation54.95605
Coefficient of variation (CV)1.6538168
Kurtosis2.8503831
Mean33.229829
Median Absolute Deviation (MAD)9
Skewness2.0295698
Sum27182
Variance3020.1674
MonotonicityNot monotonic
2024-12-10T22:28:17.320606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 145
17.7%
1 72
 
8.8%
3 65
 
7.9%
186 57
 
7.0%
23 51
 
6.2%
24 51
 
6.2%
2 45
 
5.5%
91 44
 
5.4%
19 36
 
4.4%
26 34
 
4.2%
Other values (13) 218
26.7%
ValueCountFrequency (%)
0 145
17.7%
1 72
8.8%
2 45
 
5.5%
3 65
7.9%
4 19
 
2.3%
5 25
 
3.1%
6 29
 
3.5%
8 5
 
0.6%
9 30
 
3.7%
10 18
 
2.2%
ValueCountFrequency (%)
187 20
 
2.4%
186 57
7.0%
95 15
 
1.8%
91 44
5.4%
53 4
 
0.5%
51 19
 
2.3%
44 17
 
2.1%
29 6
 
0.7%
26 34
4.2%
24 51
6.2%
Distinct100
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size56.7 KiB
2024-12-10T22:28:17.662372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length13.773839
Min length5

Characters and Unicode

Total characters11267
Distinct characters59
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)2.7%

Sample

1st rowChuukwudi
2nd rowChuukwudi
3rd rowVegetable-Market-389
4th rowProfessional_Bug2857
5th rowProfessional_Bug2857
ValueCountFrequency (%)
otherwise-log7426 57
 
7.0%
shaunk1234 51
 
6.2%
ericsfrienddave 51
 
6.2%
jimbob908 44
 
5.4%
standard_aside_2323 36
 
4.4%
rawsteak0alt 26
 
3.2%
particular_ad_7663 26
 
3.2%
cam2swag 20
 
2.4%
voidfir3 20
 
2.4%
dhhdhdhddhegeb 19
 
2.3%
Other values (90) 468
57.2%
2024-12-10T22:28:18.236777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 884
 
7.8%
a 793
 
7.0%
i 716
 
6.4%
r 640
 
5.7%
n 564
 
5.0%
o 547
 
4.9%
d 509
 
4.5%
t 495
 
4.4%
s 414
 
3.7%
h 294
 
2.6%
Other values (49) 5411
48.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11267
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 884
 
7.8%
a 793
 
7.0%
i 716
 
6.4%
r 640
 
5.7%
n 564
 
5.0%
o 547
 
4.9%
d 509
 
4.5%
t 495
 
4.4%
s 414
 
3.7%
h 294
 
2.6%
Other values (49) 5411
48.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11267
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 884
 
7.8%
a 793
 
7.0%
i 716
 
6.4%
r 640
 
5.7%
n 564
 
5.0%
o 547
 
4.9%
d 509
 
4.5%
t 495
 
4.4%
s 414
 
3.7%
h 294
 
2.6%
Other values (49) 5411
48.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11267
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 884
 
7.8%
a 793
 
7.0%
i 716
 
6.4%
r 640
 
5.7%
n 564
 
5.0%
o 547
 
4.9%
d 509
 
4.5%
t 495
 
4.4%
s 414
 
3.7%
h 294
 
2.6%
Other values (49) 5411
48.0%
Distinct124
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum2024-12-06 02:34:30
Maximum2024-12-07 11:56:27
2024-12-10T22:28:18.488961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:18.720099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

nsfw
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size946.0 B
False
818 
ValueCountFrequency (%)
False 818
100.0%
2024-12-10T22:28:18.920108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

number of comments
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.300733
Minimum1
Maximum58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-12-10T22:28:19.080549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median17
Q336
95-th percentile58
Maximum58
Range57
Interquartile range (IQR)30

Descriptive statistics

Standard deviation18.819442
Coefficient of variation (CV)0.84389339
Kurtosis-0.99103405
Mean22.300733
Median Absolute Deviation (MAD)12
Skewness0.68863331
Sum18242
Variance354.17138
MonotonicityNot monotonic
2024-12-10T22:28:19.449467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
51 102
 
12.5%
6 58
 
7.1%
58 57
 
7.0%
26 52
 
6.4%
1 44
 
5.4%
44 44
 
5.4%
3 43
 
5.3%
20 40
 
4.9%
5 39
 
4.8%
36 36
 
4.4%
Other values (15) 303
37.0%
ValueCountFrequency (%)
1 44
5.4%
2 18
 
2.2%
3 43
5.3%
4 27
3.3%
5 39
4.8%
6 58
7.1%
7 35
4.3%
8 8
 
1.0%
9 18
 
2.2%
10 30
3.7%
ValueCountFrequency (%)
58 57
7.0%
51 102
12.5%
44 44
5.4%
36 36
 
4.4%
26 52
6.4%
22 12
 
1.5%
20 40
 
4.9%
19 19
 
2.3%
18 18
 
2.2%
17 34
 
4.2%

comment id
Text

UNIQUE 

Distinct818
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size51.2 KiB
2024-12-10T22:28:19.951375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters5726
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique818 ?
Unique (%)100.0%

Sample

1st rowm0uvq87
2nd rowm0uwkv1
3rd rowm0uwjxc
4th rowm0uwk9d
5th rowm0uuxm2
ValueCountFrequency (%)
m0uvq87 1
 
0.1%
m0uon7o 1
 
0.1%
m0utb2h 1
 
0.1%
m0ut05j 1
 
0.1%
m0uwjxc 1
 
0.1%
m0uwk9d 1
 
0.1%
m0uuxm2 1
 
0.1%
m0utry8 1
 
0.1%
m0uwgix 1
 
0.1%
m0us20f 1
 
0.1%
Other values (808) 808
98.8%
2024-12-10T22:28:20.664602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
m 912
 
15.9%
0 911
 
15.9%
s 277
 
4.8%
r 237
 
4.1%
u 235
 
4.1%
t 211
 
3.7%
o 175
 
3.1%
q 157
 
2.7%
p 138
 
2.4%
n 131
 
2.3%
Other values (26) 2342
40.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5726
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
m 912
 
15.9%
0 911
 
15.9%
s 277
 
4.8%
r 237
 
4.1%
u 235
 
4.1%
t 211
 
3.7%
o 175
 
3.1%
q 157
 
2.7%
p 138
 
2.4%
n 131
 
2.3%
Other values (26) 2342
40.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5726
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
m 912
 
15.9%
0 911
 
15.9%
s 277
 
4.8%
r 237
 
4.1%
u 235
 
4.1%
t 211
 
3.7%
o 175
 
3.1%
q 157
 
2.7%
p 138
 
2.4%
n 131
 
2.3%
Other values (26) 2342
40.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5726
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
m 912
 
15.9%
0 911
 
15.9%
s 277
 
4.8%
r 237
 
4.1%
u 235
 
4.1%
t 211
 
3.7%
o 175
 
3.1%
q 157
 
2.7%
p 138
 
2.4%
n 131
 
2.3%
Other values (26) 2342
40.9%
Distinct499
Distinct (%)61.2%
Missing3
Missing (%)0.4%
Memory size55.9 KiB
2024-12-10T22:28:20.997936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length12.971779
Min length4

Characters and Unicode

Total characters10572
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique372 ?
Unique (%)45.6%

Sample

1st rowMotuProprio
2nd rowChuukwudi
3rd rowIAmRules
4th rowButterscotchSea2781
5th rowfrantizek
ValueCountFrequency (%)
automoderator 44
 
5.4%
ericsfrienddave 26
 
3.2%
shaunk1234 26
 
3.2%
standard_aside_2323 16
 
2.0%
jimbob908 12
 
1.5%
voidfir3 10
 
1.2%
contractcrazy8955 7
 
0.9%
awp_throwaway 7
 
0.9%
okneedleworker3515 7
 
0.9%
commercial-emu8846 5
 
0.6%
Other values (489) 655
80.4%
2024-12-10T22:28:21.551337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 943
 
8.9%
a 749
 
7.1%
r 691
 
6.5%
o 676
 
6.4%
i 571
 
5.4%
t 511
 
4.8%
n 498
 
4.7%
d 405
 
3.8%
s 404
 
3.8%
l 333
 
3.1%
Other values (54) 4791
45.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10572
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 943
 
8.9%
a 749
 
7.1%
r 691
 
6.5%
o 676
 
6.4%
i 571
 
5.4%
t 511
 
4.8%
n 498
 
4.7%
d 405
 
3.8%
s 404
 
3.8%
l 333
 
3.1%
Other values (54) 4791
45.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10572
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 943
 
8.9%
a 749
 
7.1%
r 691
 
6.5%
o 676
 
6.4%
i 571
 
5.4%
t 511
 
4.8%
n 498
 
4.7%
d 405
 
3.8%
s 404
 
3.8%
l 333
 
3.1%
Other values (54) 4791
45.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10572
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 943
 
8.9%
a 749
 
7.1%
r 691
 
6.5%
o 676
 
6.4%
i 571
 
5.4%
t 511
 
4.8%
n 498
 
4.7%
d 405
 
3.8%
s 404
 
3.8%
l 333
 
3.1%
Other values (54) 4791
45.3%

comment score
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.393643
Minimum-11
Maximum85
Zeros15
Zeros (%)1.8%
Negative9
Negative (%)1.1%
Memory size6.5 KiB
2024-12-10T22:28:21.767016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-11
5-th percentile1
Q11
median1
Q32
95-th percentile7
Maximum85
Range96
Interquartile range (IQR)1

Descriptive statistics

Standard deviation5.0724551
Coefficient of variation (CV)2.119136
Kurtosis116.17024
Mean2.393643
Median Absolute Deviation (MAD)0
Skewness9.177683
Sum1958
Variance25.7298
MonotonicityNot monotonic
2024-12-10T22:28:21.973883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 449
54.9%
2 168
 
20.5%
3 78
 
9.5%
4 25
 
3.1%
0 15
 
1.8%
5 15
 
1.8%
6 15
 
1.8%
7 10
 
1.2%
9 7
 
0.9%
8 4
 
0.5%
Other values (21) 32
 
3.9%
ValueCountFrequency (%)
-11 2
 
0.2%
-7 2
 
0.2%
-3 1
 
0.1%
-2 3
 
0.4%
-1 1
 
0.1%
0 15
 
1.8%
1 449
54.9%
2 168
 
20.5%
3 78
 
9.5%
4 25
 
3.1%
ValueCountFrequency (%)
85 1
 
0.1%
54 1
 
0.1%
51 1
 
0.1%
37 1
 
0.1%
35 1
 
0.1%
33 1
 
0.1%
30 1
 
0.1%
25 1
 
0.1%
18 3
0.4%
17 1
 
0.1%
Distinct785
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size305.6 KiB
2024-12-10T22:28:22.429532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3626
Median length670
Mean length252.05746
Min length2

Characters and Unicode

Total characters206183
Distinct characters157
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique775 ?
Unique (%)94.7%

Sample

1st rowExercism's top solutions are very often an unreadable condensed mess whose only "virtue" is to fit in a few lines. What you have to take from community solutions is the usage of functions that you didn't know before. Who cares if your solution is 5-10 lines longer?? What matters for learning is to try to solve it by yourself, then learn that function you didn't know it existed from the community's solutions. I guarantee you that it will stick after the "suffering".
2nd rowYes, I agree with you. Just that, If you are suffering too much to get things right, it makes me think that I might be biting more than I can chew.
3rd rowIt depends on your objective. If your object is to learn a new tech like python, then do it in python. If your object is to learn marketable skills, then yes build it in a node framework like nextjs that give you both backend and frontend tech. If you're just making a POC for the sake of it, do it which ever way you think is easiest/fastest for you. Learning is great but it comes at a cost of energy and time, all product development is a problem in resource management, so its a question of how much time/energy you have as how clear/important your goals are.
4th rowAhh.. just what the world needed. More AI trash.
5th rowOK, let's take a look... Mucho exito!
ValueCountFrequency (%)
the 1208
 
3.5%
to 1011
 
2.9%
a 818
 
2.4%
you 784
 
2.3%
and 749
 
2.2%
i 734
 
2.1%
of 527
 
1.5%
for 513
 
1.5%
it 493
 
1.4%
is 487
 
1.4%
Other values (4920) 27054
78.7%
2024-12-10T22:28:23.220248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33691
16.3%
e 17044
 
8.3%
t 14619
 
7.1%
o 13137
 
6.4%
a 11544
 
5.6%
i 10403
 
5.0%
n 10350
 
5.0%
s 9815
 
4.8%
r 8953
 
4.3%
l 6449
 
3.1%
Other values (147) 70178
34.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 206183
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
33691
16.3%
e 17044
 
8.3%
t 14619
 
7.1%
o 13137
 
6.4%
a 11544
 
5.6%
i 10403
 
5.0%
n 10350
 
5.0%
s 9815
 
4.8%
r 8953
 
4.3%
l 6449
 
3.1%
Other values (147) 70178
34.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 206183
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
33691
16.3%
e 17044
 
8.3%
t 14619
 
7.1%
o 13137
 
6.4%
a 11544
 
5.6%
i 10403
 
5.0%
n 10350
 
5.0%
s 9815
 
4.8%
r 8953
 
4.3%
l 6449
 
3.1%
Other values (147) 70178
34.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 206183
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
33691
16.3%
e 17044
 
8.3%
t 14619
 
7.1%
o 13137
 
6.4%
a 11544
 
5.6%
i 10403
 
5.0%
n 10350
 
5.0%
s 9815
 
4.8%
r 8953
 
4.3%
l 6449
 
3.1%
Other values (147) 70178
34.0%
Distinct814
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum2024-12-06 02:38:07
Maximum2024-12-07 12:28:28
2024-12-10T22:28:23.461259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:23.718804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct124
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum2024-12-06 02:34:30
Maximum2024-12-07 11:56:27
2024-12-10T22:28:23.951349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:24.229781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

spam flag
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size53.6 KiB
Not Spam
682 
Contains Embedded Link
74 
Too Short Message
 
59
Removed or Deleted Post
 
3

Length

Max length23
Median length8
Mean length9.9706601
Min length8

Characters and Unicode

Total characters8156
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot Spam
2nd rowNot Spam
3rd rowNot Spam
4th rowNot Spam
5th rowNot Spam

Common Values

ValueCountFrequency (%)
Not Spam 682
83.4%
Contains Embedded Link 74
 
9.0%
Too Short Message 59
 
7.2%
Removed or Deleted Post 3
 
0.4%

Length

2024-12-10T22:28:24.462207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-12-10T22:28:24.647778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
not 682
38.4%
spam 682
38.4%
contains 74
 
4.2%
embedded 74
 
4.2%
link 74
 
4.2%
too 59
 
3.3%
short 59
 
3.3%
message 59
 
3.3%
removed 3
 
0.2%
or 3
 
0.2%
Other values (2) 6
 
0.3%

Most occurring characters

ValueCountFrequency (%)
957
11.7%
o 942
11.5%
t 821
10.1%
a 815
10.0%
m 759
9.3%
S 741
9.1%
N 682
8.4%
p 682
8.4%
e 281
 
3.4%
d 228
 
2.8%
Other values (18) 1248
15.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8156
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
957
11.7%
o 942
11.5%
t 821
10.1%
a 815
10.0%
m 759
9.3%
S 741
9.1%
N 682
8.4%
p 682
8.4%
e 281
 
3.4%
d 228
 
2.8%
Other values (18) 1248
15.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8156
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
957
11.7%
o 942
11.5%
t 821
10.1%
a 815
10.0%
m 759
9.3%
S 741
9.1%
N 682
8.4%
p 682
8.4%
e 281
 
3.4%
d 228
 
2.8%
Other values (18) 1248
15.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8156
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
957
11.7%
o 942
11.5%
t 821
10.1%
a 815
10.0%
m 759
9.3%
S 741
9.1%
N 682
8.4%
p 682
8.4%
e 281
 
3.4%
d 228
 
2.8%
Other values (18) 1248
15.3%

is_credible
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size946.0 B
True
447 
False
371 
ValueCountFrequency (%)
True 447
54.6%
False 371
45.4%
2024-12-10T22:28:24.813636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Time Since Post
Real number (ℝ)

HIGH CORRELATION 

Distinct124
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-17.758111
Minimum-33.365833
Maximum0
Zeros2
Zeros (%)0.2%
Negative816
Negative (%)99.8%
Memory size6.5 KiB
2024-12-10T22:28:25.013764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-33.365833
5-th percentile-32.516944
Q1-27.430208
median-16.854722
Q3-11.390833
95-th percentile-1.3491667
Maximum0
Range33.365833
Interquartile range (IQR)16.039375

Descriptive statistics

Standard deviation9.5028363
Coefficient of variation (CV)-0.53512652
Kurtosis-0.91708371
Mean-17.758111
Median Absolute Deviation (MAD)6.3966667
Skewness-0.12753686
Sum-14526.135
Variance90.303897
MonotonicityDecreasing
2024-12-10T22:28:25.256098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-32.01194444 57
 
7.0%
-16.85472222 51
 
6.2%
-17.17416667 51
 
6.2%
-14.65888889 44
 
5.4%
-1.349166667 36
 
4.4%
-13.57888889 26
 
3.2%
-32.51694444 26
 
3.2%
-33.36583333 20
 
2.4%
-31.95055556 20
 
2.4%
-27.59833333 19
 
2.3%
Other values (114) 468
57.2%
ValueCountFrequency (%)
-33.36583333 20
 
2.4%
-32.51694444 26
3.2%
-32.01194444 57
7.0%
-31.95055556 20
 
2.4%
-31.92972222 7
 
0.9%
-31.88694444 6
 
0.7%
-31.41611111 1
 
0.1%
-31.30638889 5
 
0.6%
-31.19472222 3
 
0.4%
-30.57027778 4
 
0.5%
ValueCountFrequency (%)
0 2
 
0.2%
-0.1533333333 1
 
0.1%
-0.2594444444 2
 
0.2%
-0.2741666667 2
 
0.2%
-0.4116666667 1
 
0.1%
-0.465 1
 
0.1%
-0.4947222222 1
 
0.1%
-1.06 3
 
0.4%
-1.349166667 36
4.4%
-1.904722222 1
 
0.1%

Predicted post score
Real number (ℝ)

HIGH CORRELATION 

Distinct124
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.192485
Minimum3.0965853 × 10-5
Maximum162.00974
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-12-10T22:28:25.489241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0965853 × 10-5
5-th percentile5.7883642 × 10-5
Q10.0060894789
median0.076702134
Q310.424937
95-th percentile109.29643
Maximum162.00974
Range162.00971
Interquartile range (IQR)10.418847

Descriptive statistics

Standard deviation39.231775
Coefficient of variation (CV)2.0441217
Kurtosis3.1714896
Mean19.192485
Median Absolute Deviation (MAD)0.076037867
Skewness2.0332456
Sum15699.452
Variance1539.1322
MonotonicityIncreasing
2024-12-10T22:28:25.719969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
86.48035214 57
 
7.0%
0.07670213361 51
 
6.2%
0.08894711545 51
 
6.2%
0.02771066509 44
 
5.4%
5.788364232 × 10-536
 
4.4%
0.01679478556 26
 
3.2%
109.2964291 26
 
3.2%
162.0097446 20
 
2.4%
84.05353308 20
 
2.4%
11.173202 19
 
2.3%
Other values (114) 468
57.2%
ValueCountFrequency (%)
3.096585287 × 10-52
 
0.2%
3.324748275 × 10-51
 
0.1%
3.492413553 × 10-52
 
0.2%
3.516334501 × 10-52
 
0.2%
3.747810738 × 10-51
 
0.1%
3.84164326 × 10-51
 
0.1%
3.894951026 × 10-51
 
0.1%
5.062071373 × 10-53
 
0.4%
5.788364232 × 10-536
4.4%
7.489010065 × 10-51
 
0.1%
ValueCountFrequency (%)
162.0097446 20
 
2.4%
109.2964291 26
3.2%
86.48035214 57
7.0%
84.05353308 20
 
2.4%
83.24552604 7
 
0.9%
81.61068491 6
 
0.7%
65.60522292 1
 
0.1%
62.35113655 5
 
0.6%
59.20505558 3
 
0.4%
44.32191621 4
 
0.5%

Interactions

2024-12-10T22:28:13.727377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:10.182947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:11.095999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:11.973469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:12.848453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:13.920178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:10.412911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:11.273468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:12.167092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:13.029169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:14.142741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:10.551774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:11.450002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:12.327397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:13.198271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:14.304782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:10.744422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:11.621225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:12.473323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:13.389810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:14.511800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:10.904833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:11.798549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:12.663436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-12-10T22:28:13.551649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-12-10T22:28:25.880081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Predicted post scoreTime Since Postcomment scoreis_crediblenumber of commentspost scorespam flag
Predicted post score1.000-1.000-0.0280.3590.2260.1770.060
Time Since Post-1.0001.0000.0280.426-0.226-0.1770.125
comment score-0.0280.0281.0000.0890.1120.1860.000
is_credible0.3590.4260.0891.0000.6920.7920.242
number of comments0.226-0.2260.1120.6921.0000.6680.184
post score0.177-0.1770.1860.7920.6681.0000.106
spam flag0.0600.1250.0000.2420.1840.1061.000

Missing values

2024-12-10T22:28:14.782807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-12-10T22:28:15.213887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

post idpost titlepost urlpost scoreposted bypost datensfwnumber of commentscomment idcomment authorcomment scorecomment bodycomment dateparsed post datespam flagis_credibleTime Since PostPredicted post score
01h8qy7pStruggling to Retain Rust Concepts – Looking for a Book or Resource with Progressive Exerciseshttps://www.reddit.com/r/rust/comments/1h8qy7p/struggling_to_retain_rust_concepts_looking_for_a/2Chuukwudi2024-12-07 11:56:27False2m0uvq87MotuProprio3Exercism's top solutions are very often an unreadable condensed mess whose only "virtue" is to fit in a few lines.\n\n\nWhat you have to take from community solutions is the usage of functions that you didn't know before. Who cares if your solution is 5-10 lines longer?? What matters for learning is to try to solve it by yourself, then learn that function you didn't know it existed from the community's solutions. I guarantee you that it will stick after the "suffering".2024-12-07 12:05:502024-12-07 11:56:27Not SpamFalse0.0000000.000031
11h8qy7pStruggling to Retain Rust Concepts – Looking for a Book or Resource with Progressive Exerciseshttps://www.reddit.com/r/rust/comments/1h8qy7p/struggling_to_retain_rust_concepts_looking_for_a/2Chuukwudi2024-12-07 11:56:27False2m0uwkv1Chuukwudi1Yes, I agree with you. Just that, If you are suffering too much to get things right, it makes me think that I might be biting more than I can chew.2024-12-07 12:13:282024-12-07 11:56:27Not SpamFalse0.0000000.000031
21h8qth1Recommended tech stack / approach for simple hobby project?https://www.reddit.com/r/webdev/comments/1h8qth1/recommended_tech_stack_approach_for_simple_hobby/1Vegetable-Market-3892024-12-07 11:47:15False1m0uwjxcIAmRules1It depends on your objective. \nIf your object is to learn a new tech like python, then do it in python. \nIf your object is to learn marketable skills, then yes build it in a node framework like nextjs that give you both backend and frontend tech. \nIf you're just making a POC for the sake of it, do it which ever way you think is easiest/fastest for you. \n\nLearning is great but it comes at a cost of energy and time, all product development is a problem in resource management, so its a question of how much time/energy you have as how clear/important your goals are.2024-12-07 12:13:142024-12-07 11:47:15Not SpamFalse-0.1533330.000033
31h8qq89\n"Starting a New YouTube Channel for Learning Programming: Join Us to Learn Coding from Scratch!"\nhttps://www.reddit.com/r/learnprogramming/comments/1h8qq89/starting_a_new_youtube_channel_for_learning/0Professional_Bug28572024-12-07 11:40:53False2m0uwk9dButterscotchSea27811Ahh.. just what the world needed. More AI trash.2024-12-07 12:13:182024-12-07 11:40:53Not SpamFalse-0.2594440.000035
41h8qq89\n"Starting a New YouTube Channel for Learning Programming: Join Us to Learn Coding from Scratch!"\nhttps://www.reddit.com/r/learnprogramming/comments/1h8qq89/starting_a_new_youtube_channel_for_learning/0Professional_Bug28572024-12-07 11:40:53False2m0uuxm2frantizek1OK, let's take a look...\n\nMucho exito!2024-12-07 11:58:402024-12-07 11:40:53Not SpamFalse-0.2594440.000035
51h8qpsvWhat does this exception mean?https://www.reddit.com/r/learnpython/comments/1h8qpsv/what_does_this_exception_mean/1SpacefaringBanana2024-12-07 11:40:00False2m0utry8Mr-Cas3Invalid JSON. Print the input to see why it's not valid JSON.2024-12-07 11:47:572024-12-07 11:40:00Not SpamFalse-0.2741670.000035
61h8qpsvWhat does this exception mean?https://www.reddit.com/r/learnpython/comments/1h8qpsv/what_does_this_exception_mean/1SpacefaringBanana2024-12-07 11:40:00False2m0uwgixruby_alpha1As others have said, an error recognizing JSON. Looking more closely, there is something wrong at the very beginning of the file data. Your JSON file might be empty.2024-12-07 12:12:232024-12-07 11:40:00Not SpamFalse-0.2741670.000035
71h8qlqbAre you feeling overwhelmed with exams, quizzes, or assignments? Struggling to keep up in your classes? Look no further! I’m here to provide the academic support you need to excel.https://www.reddit.com/r/homeworkhelpNY/comments/1h8qlqb/are_you_feeling_overwhelmed_with_exams_quizzes_or/1Eddy-Aioli-592024-12-07 11:31:45False1m0us20fAutoModerator1Join our Discord server to connect with the community: [Discord Invite Link](https://discord.gg/a2kGCwufzg)\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/homeworkhelpNY) if you have any questions or concerns.*2024-12-07 11:31:452024-12-07 11:31:45Contains Embedded LinkFalse-0.4116670.000037
81h8qk4aAre you feeling overwhelmed with exams, quizzes, or assignments? Struggling to keep up in your classes? Look no further! I’m here to provide the academic support you need to excel.https://www.reddit.com/r/HomeworkHelp_Reddit/comments/1h8qk4a/are_you_feeling_overwhelmed_with_exams_quizzes_or/1Eddy-Aioli-592024-12-07 11:28:33False1m0urqbyAutoModerator1\nPlease reach out to u/Calixta2_02 for online Homework/Exams/Tests/Assignments/Quiz Help. We promise to provide quality homework assistance with trusted experts. We value your Privacy---Confidentiality Guaranteed. Please join our subreddit r/HomeworkHelp_Reddit and stay connected with us. Also, you can contact to by email:\n\n* **Email ID:** homeworkhelpreddit67@gmail.com\n\n* Thank you!\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/HomeworkHelp_Reddit) if you have any questions or concerns.*2024-12-07 11:28:342024-12-07 11:28:33Not SpamFalse-0.4650000.000038
91h8qj8cAre you feeling overwhelmed with exams, quizzes, or assignments? Struggling to keep up in your classes? Look no further! I’m here to provide the academic support you need to excel.https://www.reddit.com/r/HomeworkHelp_Reddit/comments/1h8qj8c/are_you_feeling_overwhelmed_with_exams_quizzes_or/1Eddy-Aioli-592024-12-07 11:26:46False1m0urjmaAutoModerator1\nPlease reach out to u/Calixta2_02 for online Homework/Exams/Tests/Assignments/Quiz Help. We promise to provide quality homework assistance with trusted experts. We value your Privacy---Confidentiality Guaranteed. Please join our subreddit r/HomeworkHelp_Reddit and stay connected with us. Also, you can contact to by email:\n\n* **Email ID:** homeworkhelpreddit67@gmail.com\n\n* Thank you!\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/HomeworkHelp_Reddit) if you have any questions or concerns.*2024-12-07 11:26:462024-12-07 11:26:46Not SpamFalse-0.4947220.000039
post idpost titlepost urlpost scoreposted bypost datensfwnumber of commentscomment idcomment authorcomment scorecomment bodycomment dateparsed post datespam flagis_credibleTime Since PostPredicted post score
8081h7qzcjFirst attempt at game designhttps://v.redd.it/jho9xmm5455e1187cam2swag2024-12-06 02:34:30False20m0pfgigPaperalizadoYT1It sure looks like a game.2024-12-06 13:46:512024-12-06 02:34:30Not SpamTrue-33.365833162.009745
8091h7qzcjFirst attempt at game designhttps://v.redd.it/jho9xmm5455e1187cam2swag2024-12-06 02:34:30False20m0pipcnchrissolanilla1When will it be on steam early access?2024-12-06 14:08:002024-12-06 02:34:30Not SpamTrue-33.365833162.009745
8101h7qzcjFirst attempt at game designhttps://v.redd.it/jho9xmm5455e1187cam2swag2024-12-06 02:34:30False20m0pz59tValuable_Spell_121An air dashing frog. Pretty cool2024-12-06 15:42:532024-12-06 02:34:30Not SpamTrue-33.365833162.009745
8111h7qzcjFirst attempt at game designhttps://v.redd.it/jho9xmm5455e1187cam2swag2024-12-06 02:34:30False20m0q2rt1sea_stones1When you fell off the platform, I thought "no death plane?"\nThen you popped back and I was like "they thought of everything!"\n\nLooking good. Looks coherent. Better than the mess of "implement thing now, figure out why later" I'm on. Good luck!2024-12-06 16:02:082024-12-06 02:34:30Not SpamTrue-33.365833162.009745
8121h7qzcjFirst attempt at game designhttps://v.redd.it/jho9xmm5455e1187cam2swag2024-12-06 02:34:30False20m0q4syhNext-Palpitation1521Yeah that is true that you are diving into some stuff and making it cool2024-12-06 16:13:022024-12-06 02:34:30Not SpamTrue-33.365833162.009745
8131h7qzcjFirst attempt at game designhttps://v.redd.it/jho9xmm5455e1187cam2swag2024-12-06 02:34:30False20m0qv2udAmilcarMen1You gonna love AnimationTree in couple of days ! Keep Up the good work !2024-12-06 18:29:582024-12-06 02:34:30Not SpamTrue-33.365833162.009745
8141h7qzcjFirst attempt at game designhttps://v.redd.it/jho9xmm5455e1187cam2swag2024-12-06 02:34:30False20m0sw590FinalStanZ1Green guy from garten of Banban2024-12-07 01:30:372024-12-06 02:34:30Not SpamTrue-33.365833162.009745
8151h7qzcjFirst attempt at game designhttps://v.redd.it/jho9xmm5455e1187cam2swag2024-12-06 02:34:30False20m0to9moWaste_Consequence3631Interesting concept 🤔2024-12-07 04:50:402024-12-06 02:34:30Too Short MessageTrue-33.365833162.009745
8161h7qzcjFirst attempt at game designhttps://v.redd.it/jho9xmm5455e1187cam2swag2024-12-06 02:34:30False20m0u40cprwp801that frog needs a gatling gun2024-12-07 07:13:352024-12-06 02:34:30Not SpamTrue-33.365833162.009745
8171h7qzcjFirst attempt at game designhttps://v.redd.it/jho9xmm5455e1187cam2swag2024-12-06 02:34:30False20m0u7avrjon118881I've watched so many videos about game design while neglecting the practice videos (and even more important, the actual practice.)\n\nI'm catching up on the parts I've been neglecting, but it's important to maintain a balance, as too much focus on either approach can leave some weaknesses that take time to get past.2024-12-07 07:48:442024-12-06 02:34:30Not SpamTrue-33.365833162.009745